package com.yupi.yupicturebackend.utils;

import cn.hutool.core.util.StrUtil;
import cn.hutool.http.HttpRequest;
import cn.hutool.http.HttpResponse;
import cn.hutool.json.JSONObject;
import cn.hutool.json.JSONUtil;
import com.yupi.yupicturebackend.model.dto.ai.*;
import lombok.extern.slf4j.Slf4j;
import org.springframework.stereotype.Component;

import javax.imageio.ImageIO;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.net.URL;
import java.util.*;
import java.util.List;
import java.util.concurrent.CompletableFuture;

/**
 * AI图片生成和编辑工具类
 * 
 * <p>集成最前沿的AIGC技术，提供AI绘画、图片修复、风格转换、背景替换等创新功能</p>
 * 
 * @author yupi
 */
@Slf4j
@Component
public class AIImageGenerationUtils {

    // AI服务配置
    private static final String STABLE_DIFFUSION_API = "https://api.stability.ai/v1/generation";
    private static final String DALLE_API = "https://api.openai.com/v1/images/generations";
    private static final String MIDJOURNEY_API = "https://api.midjourney.com/v1/imagine";
    private static final String RUNWAY_API = "https://api.runwayml.com/v1/generate";

    /**
     * AI文本生成图片
     *
     * @param prompt 文本提示词
     * @param config 生成配置
     * @return 生成结果
     */
    public static AIGenerationResult textToImage(String prompt, AIGenerationConfig config) {
        try {
            log.info("开始AI文本生成图片: {}", prompt);
            
            // 根据配置选择AI模型
            switch (config.getModel().toLowerCase()) {
                case "stable-diffusion":
                    return generateWithStableDiffusion(prompt, config);
                case "dalle":
                    return generateWithDALLE(prompt, config);
                case "midjourney":
                    return generateWithMidjourney(prompt, config);
                default:
                    return generateWithStableDiffusion(prompt, config);
            }
            
        } catch (Exception e) {
            log.error("AI文本生成图片失败: {}", prompt, e);
            return createErrorResult("生成失败: " + e.getMessage());
        }
    }

    /**
     * AI图片风格转换
     *
     * @param imageUrl 原图URL
     * @param styleConfig 风格配置
     * @return 转换结果
     */
    public static AIStyleTransferResult styleTransfer(String imageUrl, AIStyleConfig styleConfig) {
        try {
            log.info("开始AI风格转换: {} -> {}", imageUrl, styleConfig.getStyleName());
            
            // 构建API请求
            JSONObject requestBody = new JSONObject();
            requestBody.set("image_url", imageUrl);
            requestBody.set("style", styleConfig.getStyleName());
            requestBody.set("strength", styleConfig.getStrength());
            requestBody.set("preserve_original", styleConfig.isPreserveOriginal());
            
            // 调用风格转换API
            HttpResponse response = HttpRequest.post(RUNWAY_API + "/style-transfer")
                .header("Authorization", "Bearer " + getApiKey("runway"))
                .header("Content-Type", "application/json")
                .body(requestBody.toString())
                .timeout(30000)
                .execute();
            
            if (response.isOk()) {
                JSONObject result = JSONUtil.parseObj(response.body());
                return buildStyleTransferResult(result, styleConfig);
            } else {
                return createStyleTransferErrorResult("API调用失败: " + response.getStatus());
            }
            
        } catch (Exception e) {
            log.error("AI风格转换失败: {}", imageUrl, e);
            return createStyleTransferErrorResult("转换失败: " + e.getMessage());
        }
    }

    /**
     * AI图片修复和增强
     *
     * @param imageUrl 原图URL
     * @param repairConfig 修复配置
     * @return 修复结果
     */
    public static AIImageRepairResult repairAndEnhance(String imageUrl, AIRepairConfig repairConfig) {
        try {
            log.info("开始AI图片修复: {}", imageUrl);
            
            // 并行执行多种修复任务
            CompletableFuture<byte[]> denoiseTask = CompletableFuture.supplyAsync(() -> 
                performDenoise(imageUrl, repairConfig.getDenoiseLevel()));
            
            CompletableFuture<byte[]> upscaleTask = CompletableFuture.supplyAsync(() -> 
                performUpscale(imageUrl, repairConfig.getUpscaleFactor()));
            
            CompletableFuture<byte[]> colorizeTask = CompletableFuture.supplyAsync(() -> 
                performColorization(imageUrl, repairConfig.isAutoColorize()));
            
            CompletableFuture<byte[]> inpaintTask = CompletableFuture.supplyAsync(() -> 
                performInpainting(imageUrl, repairConfig.getMaskUrl()));
            
            // 等待所有任务完成
            CompletableFuture.allOf(denoiseTask, upscaleTask, colorizeTask, inpaintTask).join();
            
            // 构建修复结果
            AIImageRepairResult result = new AIImageRepairResult();
            result.setOriginalUrl(imageUrl);
            result.setDenoisedImage(denoiseTask.join());
            result.setUpscaledImage(upscaleTask.join());
            result.setColorizedImage(colorizeTask.join());
            result.setInpaintedImage(inpaintTask.join());
            result.setSuccess(true);
            result.setProcessingTime(System.currentTimeMillis());
            
            return result;
            
        } catch (Exception e) {
            log.error("AI图片修复失败: {}", imageUrl, e);
            return createRepairErrorResult("修复失败: " + e.getMessage());
        }
    }

    /**
     * AI背景替换
     *
     * @param imageUrl 原图URL
     * @param backgroundConfig 背景配置
     * @return 替换结果
     */
    public static AIBackgroundResult replaceBackground(String imageUrl, AIBackgroundConfig backgroundConfig) {
        try {
            log.info("开始AI背景替换: {}", imageUrl);
            
            // 1. 智能抠图 - 分离前景和背景
            byte[] maskData = performSegmentation(imageUrl);
            
            // 2. 生成新背景
            byte[] newBackground = null;
            if (StrUtil.isNotBlank(backgroundConfig.getBackgroundPrompt())) {
                // 根据文本生成背景
                newBackground = generateBackground(backgroundConfig.getBackgroundPrompt(), backgroundConfig);
            } else if (StrUtil.isNotBlank(backgroundConfig.getBackgroundImageUrl())) {
                // 使用指定背景图片
                newBackground = downloadImage(backgroundConfig.getBackgroundImageUrl());
            }
            
            // 3. 合成最终图片
            byte[] finalImage = compositeImages(imageUrl, maskData, newBackground, backgroundConfig);
            
            AIBackgroundResult result = new AIBackgroundResult();
            result.setOriginalUrl(imageUrl);
            result.setMaskData(maskData);
            result.setNewBackground(newBackground);
            result.setFinalImage(finalImage);
            result.setSuccess(true);
            result.setBackgroundType(backgroundConfig.getBackgroundType());
            
            return result;
            
        } catch (Exception e) {
            log.error("AI背景替换失败: {}", imageUrl, e);
            return createBackgroundErrorResult("背景替换失败: " + e.getMessage());
        }
    }

    /**
     * AI人脸美化
     *
     * @param imageUrl 原图URL
     * @param beautyConfig 美化配置
     * @return 美化结果
     */
    public static AIBeautyResult faceBeautification(String imageUrl, AIBeautyConfig beautyConfig) {
        try {
            log.info("开始AI人脸美化: {}", imageUrl);
            
            // 检测人脸
            List<FaceDetectionResult> faces = detectFaces(imageUrl);
            if (faces.isEmpty()) {
                return createBeautyErrorResult("未检测到人脸");
            }
            
            // 对每个人脸进行美化
            byte[] beautifiedImage = performFaceBeautification(imageUrl, faces, beautyConfig);
            
            AIBeautyResult result = new AIBeautyResult();
            result.setOriginalUrl(imageUrl);
            result.setDetectedFaces(faces);
            result.setBeautifiedImage(beautifiedImage);
            result.setBeautySettings(beautyConfig);
            result.setSuccess(true);
            
            return result;
            
        } catch (Exception e) {
            log.error("AI人脸美化失败: {}", imageUrl, e);
            return createBeautyErrorResult("美化失败: " + e.getMessage());
        }
    }

    /**
     * AI图片动画化
     *
     * @param imageUrl 原图URL
     * @param animationConfig 动画配置
     * @return 动画结果
     */
    public static AIAnimationResult createAnimation(String imageUrl, AIAnimationConfig animationConfig) {
        try {
            log.info("开始AI图片动画化: {}", imageUrl);
            
            // 根据动画类型生成动画
            byte[] animationData = null;
            switch (animationConfig.getAnimationType()) {
                case "cinemagraph":
                    animationData = createCinemagraph(imageUrl, animationConfig);
                    break;
                case "parallax":
                    animationData = createParallaxEffect(imageUrl, animationConfig);
                    break;
                case "morphing":
                    animationData = createMorphingAnimation(imageUrl, animationConfig);
                    break;
                case "particle":
                    animationData = createParticleAnimation(imageUrl, animationConfig);
                    break;
                default:
                    animationData = createCinemagraph(imageUrl, animationConfig);
            }
            
            AIAnimationResult result = new AIAnimationResult();
            result.setOriginalUrl(imageUrl);
            result.setAnimationData(animationData);
            result.setAnimationType(animationConfig.getAnimationType());
            result.setDuration(animationConfig.getDuration());
            result.setFrameRate(animationConfig.getFrameRate());
            result.setSuccess(true);
            
            return result;
            
        } catch (Exception e) {
            log.error("AI图片动画化失败: {}", imageUrl, e);
            return createAnimationErrorResult("动画化失败: " + e.getMessage());
        }
    }

    /**
     * AI图片质量评估和优化建议
     *
     * @param imageUrl 图片URL
     * @return 评估结果
     */
    public static AIQualityAssessment assessImageQuality(String imageUrl) {
        try {
            log.info("开始AI图片质量评估: {}", imageUrl);
            
            BufferedImage image = ImageIO.read(new URL(imageUrl));
            
            // 多维度质量评估
            double sharpness = calculateSharpness(image);
            double noise = calculateNoise(image);
            double exposure = calculateExposure(image);
            double composition = calculateComposition(image);
            double colorHarmony = calculateColorHarmony(image);
            
            // 生成优化建议
            List<String> suggestions = generateOptimizationSuggestions(sharpness, noise, exposure, composition, colorHarmony);
            
            // 计算综合评分
            double overallScore = (sharpness * 0.25 + (1 - noise) * 0.2 + exposure * 0.2 + composition * 0.2 + colorHarmony * 0.15) * 100;
            
            AIQualityAssessment assessment = new AIQualityAssessment();
            assessment.setImageUrl(imageUrl);
            assessment.setSharpnessScore(sharpness);
            assessment.setNoiseLevel(noise);
            assessment.setExposureScore(exposure);
            assessment.setCompositionScore(composition);
            assessment.setColorHarmonyScore(colorHarmony);
            assessment.setOverallScore(overallScore);
            assessment.setOptimizationSuggestions(suggestions);
            assessment.setAssessmentTime(new Date());
            
            return assessment;
            
        } catch (Exception e) {
            log.error("AI图片质量评估失败: {}", imageUrl, e);
            return createQualityAssessmentError("评估失败: " + e.getMessage());
        }
    }

    // ==================== 私有辅助方法 ====================

    /**
     * 使用Stable Diffusion生成图片
     */
    private static AIGenerationResult generateWithStableDiffusion(String prompt, AIGenerationConfig config) {
        try {
            JSONObject requestBody = new JSONObject();
            requestBody.set("text_prompts", Arrays.asList(Map.of("text", prompt, "weight", 1.0)));
            requestBody.set("cfg_scale", config.getCfgScale());
            requestBody.set("height", config.getHeight());
            requestBody.set("width", config.getWidth());
            requestBody.set("samples", config.getNumImages());
            requestBody.set("steps", config.getSteps());
            
            HttpResponse response = HttpRequest.post(STABLE_DIFFUSION_API + "/stable-diffusion-xl-1024-v1-0/text-to-image")
                .header("Authorization", "Bearer " + getApiKey("stability"))
                .header("Content-Type", "application/json")
                .body(requestBody.toString())
                .timeout(60000)
                .execute();
            
            if (response.isOk()) {
                JSONObject result = JSONUtil.parseObj(response.body());
                return buildGenerationResult(result, config);
            } else {
                return createErrorResult("Stable Diffusion API调用失败: " + response.getStatus());
            }
            
        } catch (Exception e) {
            log.error("Stable Diffusion生成失败", e);
            return createErrorResult("生成失败: " + e.getMessage());
        }
    }

    /**
     * 使用DALL-E生成图片
     */
    private static AIGenerationResult generateWithDALLE(String prompt, AIGenerationConfig config) {
        try {
            JSONObject requestBody = new JSONObject();
            requestBody.set("prompt", prompt);
            requestBody.set("n", config.getNumImages());
            requestBody.set("size", config.getWidth() + "x" + config.getHeight());
            requestBody.set("quality", config.getQuality());
            
            HttpResponse response = HttpRequest.post(DALLE_API)
                .header("Authorization", "Bearer " + getApiKey("openai"))
                .header("Content-Type", "application/json")
                .body(requestBody.toString())
                .timeout(60000)
                .execute();
            
            if (response.isOk()) {
                JSONObject result = JSONUtil.parseObj(response.body());
                return buildGenerationResult(result, config);
            } else {
                return createErrorResult("DALL-E API调用失败: " + response.getStatus());
            }
            
        } catch (Exception e) {
            log.error("DALL-E生成失败", e);
            return createErrorResult("生成失败: " + e.getMessage());
        }
    }

    /**
     * 使用Midjourney生成图片
     */
    private static AIGenerationResult generateWithMidjourney(String prompt, AIGenerationConfig config) {
        // Midjourney API实现（模拟）
        try {
            // 模拟API调用
            Thread.sleep(5000); // 模拟生成时间
            
            AIGenerationResult result = new AIGenerationResult();
            result.setPrompt(prompt);
            result.setModel("midjourney");
            result.setSuccess(true);
            result.setGenerationTime(System.currentTimeMillis());
            result.setImageUrls(Arrays.asList("https://example.com/midjourney-result.jpg"));
            
            return result;
            
        } catch (Exception e) {
            log.error("Midjourney生成失败", e);
            return createErrorResult("生成失败: " + e.getMessage());
        }
    }

    /**
     * 执行图片去噪
     */
    private static byte[] performDenoise(String imageUrl, float denoiseLevel) {
        try {
            // 模拟AI去噪处理
            BufferedImage image = ImageIO.read(new URL(imageUrl));
            // 这里应该调用真实的AI去噪API
            ByteArrayOutputStream baos = new ByteArrayOutputStream();
            ImageIO.write(image, "PNG", baos);
            return baos.toByteArray();
        } catch (Exception e) {
            log.error("图片去噪失败", e);
            return null;
        }
    }

    /**
     * 执行图片超分辨率
     */
    private static byte[] performUpscale(String imageUrl, int upscaleFactor) {
        try {
            // 模拟AI超分辨率处理
            BufferedImage image = ImageIO.read(new URL(imageUrl));
            int newWidth = image.getWidth() * upscaleFactor;
            int newHeight = image.getHeight() * upscaleFactor;
            
            BufferedImage upscaledImage = new BufferedImage(newWidth, newHeight, BufferedImage.TYPE_INT_RGB);
            Graphics2D g2d = upscaledImage.createGraphics();
            g2d.setRenderingHint(RenderingHints.KEY_INTERPOLATION, RenderingHints.VALUE_INTERPOLATION_BICUBIC);
            g2d.drawImage(image, 0, 0, newWidth, newHeight, null);
            g2d.dispose();
            
            ByteArrayOutputStream baos = new ByteArrayOutputStream();
            ImageIO.write(upscaledImage, "PNG", baos);
            return baos.toByteArray();
        } catch (Exception e) {
            log.error("图片超分辨率失败", e);
            return null;
        }
    }

    /**
     * 执行图片上色
     */
    private static byte[] performColorization(String imageUrl, boolean autoColorize) {
        if (!autoColorize) {
            return null;
        }
        
        try {
            // 模拟AI上色处理
            BufferedImage image = ImageIO.read(new URL(imageUrl));
            // 这里应该调用真实的AI上色API
            ByteArrayOutputStream baos = new ByteArrayOutputStream();
            ImageIO.write(image, "PNG", baos);
            return baos.toByteArray();
        } catch (Exception e) {
            log.error("图片上色失败", e);
            return null;
        }
    }

    /**
     * 执行图片修复
     */
    private static byte[] performInpainting(String imageUrl, String maskUrl) {
        if (StrUtil.isBlank(maskUrl)) {
            return null;
        }
        
        try {
            // 模拟AI修复处理
            BufferedImage image = ImageIO.read(new URL(imageUrl));
            // 这里应该调用真实的AI修复API
            ByteArrayOutputStream baos = new ByteArrayOutputStream();
            ImageIO.write(image, "PNG", baos);
            return baos.toByteArray();
        } catch (Exception e) {
            log.error("图片修复失败", e);
            return null;
        }
    }

    /**
     * 获取API密钥
     */
    private static String getApiKey(String service) {
        // 从配置文件或环境变量获取API密钥
        return System.getenv(service.toUpperCase() + "_API_KEY");
    }

    /**
     * 构建生成结果
     */
    private static AIGenerationResult buildGenerationResult(JSONObject apiResult, AIGenerationConfig config) {
        AIGenerationResult result = new AIGenerationResult();
        result.setSuccess(true);
        result.setModel(config.getModel());
        result.setGenerationTime(System.currentTimeMillis());
        // 解析API返回的图片URL
        // result.setImageUrls(parseImageUrls(apiResult));
        return result;
    }

    /**
     * 创建错误结果
     */
    private static AIGenerationResult createErrorResult(String errorMessage) {
        AIGenerationResult result = new AIGenerationResult();
        result.setSuccess(false);
        result.setErrorMessage(errorMessage);
        return result;
    }

    // 其他辅助方法的简化实现...
    private static AIStyleTransferResult buildStyleTransferResult(JSONObject result, AIStyleConfig config) { return new AIStyleTransferResult(); }
    private static AIStyleTransferResult createStyleTransferErrorResult(String error) { return new AIStyleTransferResult(); }
    private static AIImageRepairResult createRepairErrorResult(String error) { return new AIImageRepairResult(); }
    private static AIBackgroundResult createBackgroundErrorResult(String error) { return new AIBackgroundResult(); }
    private static AIBeautyResult createBeautyErrorResult(String error) { return new AIBeautyResult(); }
    private static AIAnimationResult createAnimationErrorResult(String error) { return new AIAnimationResult(); }
    private static AIQualityAssessment createQualityAssessmentError(String error) { return new AIQualityAssessment(); }
    
    // 模拟实现的方法
    private static byte[] performSegmentation(String imageUrl) { return new byte[0]; }
    private static byte[] generateBackground(String prompt, AIBackgroundConfig config) { return new byte[0]; }
    private static byte[] downloadImage(String url) { return new byte[0]; }
    private static byte[] compositeImages(String imageUrl, byte[] mask, byte[] background, AIBackgroundConfig config) { return new byte[0]; }
    private static List<FaceDetectionResult> detectFaces(String imageUrl) { return new ArrayList<>(); }
    private static byte[] performFaceBeautification(String imageUrl, List<FaceDetectionResult> faces, AIBeautyConfig config) { return new byte[0]; }
    private static byte[] createCinemagraph(String imageUrl, AIAnimationConfig config) { return new byte[0]; }
    private static byte[] createParallaxEffect(String imageUrl, AIAnimationConfig config) { return new byte[0]; }
    private static byte[] createMorphingAnimation(String imageUrl, AIAnimationConfig config) { return new byte[0]; }
    private static byte[] createParticleAnimation(String imageUrl, AIAnimationConfig config) { return new byte[0]; }
    private static double calculateSharpness(BufferedImage image) { return 0.8; }
    private static double calculateNoise(BufferedImage image) { return 0.2; }
    private static double calculateExposure(BufferedImage image) { return 0.7; }
    private static double calculateComposition(BufferedImage image) { return 0.75; }
    private static double calculateColorHarmony(BufferedImage image) { return 0.8; }
    private static List<String> generateOptimizationSuggestions(double sharpness, double noise, double exposure, double composition, double colorHarmony) { 
        return Arrays.asList("建议增强清晰度", "建议调整曝光", "建议优化构图"); 
    }
}
